| Autor: |
Ahmed Abada, Marc St-Hilaire, and Wei Shi |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
IEEE Access, Vol 12, Pp 172969-172979 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2169-3536 |
| DOI: |
10.1109/ACCESS.2024.3493012 |
| Popis: |
Revenue optimization is a main consideration in auction design. While it is a first-order objective in most auction settings, that is not the case for rebate auctions that use monetary rewards to incentivize auction participants to perform a task, where revenue optimization is secondary to successful task completion. This paper considers the case of VCG-based rebate auctions used to incentivize cloud workload migrations between datacenters to correct power-grid energy imbalances, and proposes a revenue maximization approach that takes into account the task completion objective (i.e., power-grid balancing) before a specified deadline. The proposed approach uses a task-completion constraint in the rebate auction optimization problem to ensure that the required task is completed on time, and uses predictions for the trend of future bid valuations (assumed to be gathered via a separate prediction module) to adjust the task-completion constraint to maximize revenue. Existing VCG-based revenue maximization approaches are not suitable for rebate auctions since they do not consider task completion deadlines (as regular auctions are not associated with tasks), and assume that bid valuations are randomly drawn from a probability distribution, which is not the case in rebate auctions. The proposed approach is compared against the existing rebate auction implementation (that does not consider the task completion deadline, nor the variations in bid valuations over time) in terms of its monetary effect on the auction participants and its ability to complete the required task on time. Simulation results show that the proposed approach improves the auctioneer’s revenue and consistently completes the energy-balancing task on time. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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